Don’t waste evidence on the youth! Recent data highlights education and employment trends

A recent New York Times article describes a major contemporary challenge facing governments: the world has too many young people. A quarter of the world’s population is young (ages 10-24), and the majority live in developing countries. Policymakers are struggling with high levels of youth unemployment in every country, but a key challenge in developing countries has been a lack of data on education and employment characteristics. To fill this evidence gap, FHI 360’s Education Policy and Data Center (EPDC) recently added country-level Youth Education and Employment profiles to the resources available on our website. In this post, I describe the data and how they were collected, and I give some examples of how these data can be used to inform policymaking and program design.

What are the Youth Education and Employment profiles?

The EPDC Youth Education and Employment profiles present the most recent country-level education and employment characteristics for youth ages 15-29, including education enrollment, unemployment, labor force status, length of time transitioning to work, and earnings. The profiles are also available for download as PDF files which contain additional breakdowns by equity dimension such as gender and socioeconomic status.

The EPDC profiles are built upon publicly-available data taken from the School-to-Work Transition Survey (SWTS), a collaborative effort between the International Labour Organization (ILO) and the MasterCard Foundation. SWTS works with national statistical bodies across 32 countries to administer representative surveys for measuring youth employment, educational attainment, and schooling of youth.

How can the youth profiles be used?

We have compiled the EPDC profiles to point users toward information that can better inform policymaking and program design. Here are two hypothetical examples of how the profiles might be used.

Figure 1: Transition length in months, by education attainment – Jamaica, 2015

Figure 1: Transition length in months, by education attainment – Jamaica, 2015

In example one, let’s say that you are working in the Ministry of Education in Jamaica and overseeing the roll out of a jobs training program for out-of-school youth. The profiles present earnings data by age and level of education, as well as length of transition (job search time) between finishing education and beginning a job (see figure 1). Using the profile data, you can see that the real challenge in making the school-to-work transition is for people who only have a primary education. Practitioners might use this information to tailor trainings to the specific educational background of participants.

Figure 2: Labor force status by education attainment and gender, not in school – Lebanon, 2015

Figure 2: Labor force status by education attainment and gender, not in school – Lebanon, 2015

In example two, let’s say you are working with a non-profit foundation based in the Middle East to launch a research initiative on youth labor market inactivity across countries. Those with knowledge of youth labor market conditions are likely aware that aggregate statistics often mask substantial disparities in outcomes by subgroup. The profiles break down key indicators by gender and socioeconomic status, showing that for example in Lebanon the inactivity rate (the percentage of youth who are not in school and not in the labor force) is 1.6% for males with a university degree but 37.8% for females with the same level of education (see figure 2). This disparity compares to a country-level average of 20%, and is evidence of the strong bias in hiring faced by women in many low- and middle-income countries.

Like all data, the SWTS data has limitations. For example, the SWTS does not include a literacy or skills assessment component, similar to the World Bank’s STEP surveys. Such information is critical for assessing educational background in terms of attainment but also how knowledge and skills interact with opportunities and employment conditions to produce outcomes. Additionally, the SWTS data utilize relatively small samples and lack standardization across countries, which can present challenges in analyzing global trends.

While policymakers and researchers continue to mine the SWTS data for evidence to inform research on youth policies and programming, the EPDC profiles provide users with a jump-start on the evidence. For those interested in exploring the profiles, you can use the interactive Tableau dashboards or the printable PDF profiles. Let us know in the comments section how you are using the data.

Image credit: FHI 360

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